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Runthala, A.

Publications and source records attributed to Runthala, A..

3 recordsLinked to original sources

NudF-boosted strategy to improve the yield of DXS pathway

BackgroundTerpenoids form a large pool of highly diverse organic compounds possessing several economically important properties, including nutritional, aromatic, and pharmacological properties. The DXP pathways end enzyme, nuclear distribution protein (NudF), interacting with isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP), is critical for the synthesis of isoprenol/prenol/downstream compounds. The enzyme is yet to be thoroughly investigated to increase the overall yield of terpenoids in the Bacillus subtilis, which is widely used in industry and is generally regarded as safe (GRAS) bacterium. The study aims to analyze the evolutionary conservation across the active site, and map the key residues for mutagenesis studies. The study would allow us customize the metabolic load towards the synthesis of prenol or isoprenol or any of the downstream molecules. ResultsThe 37-sequence dataset, extracted from 103 Bacillus subtilis entries, show a high phylogenetic divergence, and only six one-motif sequences ASB92783.1, ASB69297.1, ASB56714.1, AOR97677.1, AOL97023.1, and OAZ71765.1 show monophyly relationship, unlike a complete polyphyly relationship between the other 31 three-motif sequences. Further, only 47 of 179 residues of the representative sequence CUB50584.1 are observed to be significantly conserved. Docking analysis shows a preferential bias of ADP-ribose pyrophosphatase towards IPP, and a nearly 3-fold energetic difference is observed between IPP and DMAPP. Computational saturation mutagenesis of the seven hotspot residues identifies two key positions LYS78 and PHE116, encoded within loop1 and loop7, majorly interact with the ligands DMAPP and IPP, and their mutants K78I/K78L and PHE116D/PHE116E are found to stabilize the overall conformation. The loops are hereby shown to play a regulatory role in guiding the promiscuity of NudF towards a specific ligand. ConclusionThe study map the phylogenetic relationship between the 37 representative B.subtiis NudF sequences, and through sequence conservation, structural contact map, topological flexibility, and saturation mutagenesis of the active site residues, the essential residues regulating the interaction of NudF with IPP/DMAPP are deciphered. The study robustly screens its mutational landscape and localizes the two crucial residues LYS78 and PHE116 for directing the mutagenesis studies. The preliminary docking and simulation results also suggest a preferential bias of ADP-ribose pyrophosphatase towards IPP over DMAPP. The findings would pave the way for the development of novel enzyme variants with highly improved catalytic ability for the large-scale bioproduction of specific terpenoids with significant neutraceutical or commercial value.

bioengineering↗

Current strategic limitations of phylogenetic tools badly impact the inference of an evolutionary tree

For drawing an evolutionary relationship among several protein sequences, the phylogenetic tree is usually constructed through maximum likelihood-based algorithms. To improve the accuracy of these methodologies, many parameters like bootstrap methods, correlation coefficient and residue-substitution models are presumably over-ranked to derive biologically credible relationships. Although the accuracy of protein sequence alignment and the substitution matrix are preliminary constraints to define the biological accuracy of the overlapped sequences/residues, the alignment is not iteratively optimized through the statistical testing of residue-substitution models. The study majorly highlights the potential pitfalls that significantly affect the accuracy of an evolutionary protocol. It emphasizes the need for a more accurate scrutiny of the entire phylogenetic methodology. The need of iterative optimizations is illustrated to construct a biologically credible and not mathematically optimal tree for a sequence dataset.

evolutionary biology↗

Probabilistic divergence of a TBM methodology from the ideal protocol

Protein structural information is essential for the detailed mapping of a functional protein network. For a higher modelling accuracy and quicker implementation, template based algorithms have been extensively deployed and redefined. The methods only assess the predicted structure against its native state/template, and do not estimate the accuracy for each modelling step. A divergence measure is postulated to estimate the modelling accuracy against its theoretical optimal benchmark. By freezing the domain boundaries, the divergence measures are predicted for the most crucial steps of a modelling algorithm. To precisely refine the score using weighting constants, big data analysis could further be deployed.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioinformatics↗